Now a study by Robert Eckel and colleagues, published in Current Biology, illustrates how sleep deprivation and timing of meals can markedly alter insulin sensitivity.
Studies were conducted in 16 healthy young adults (8w) with normal BMI. Following a week of 9-hr-per-night sleep schedules, subjects were studied in a crossover counterbalanced design with 9-hr-per-night adequate sleep (9-hr) and 5-hr-per-night short sleep duration (5-hr) conditions lasting 5 days each, to simulate a 5-day work week. Sleep was restricted by delaying bedtime and advancing wake time by 2 hr each.
Energy balanced diets continued during baseline, whereas food intake was ad libitum during scheduled wakefulness of 5- and 9-hr conditions.
Overall, the simulated 5-day work week of 5-hr-per-night sleep together with an ad libitum diet resulted in a 20% decrease in oral and intravenous insulin sensitivity, which was compensated for by increased insulin secretion..
These changes persisted for up to 5 days after restoring 9-hr sleep opportunities.
The authors also showed that shifting circadian rhythm resulted in morning wakefulness and eating during the biological night, a factor that may promote weight gain over time.
According to conventional wisdom, beverages with artificial sweeteners should be weight neutral, given that they do not contain calories. However, whether this is true or not remains controversial. Besides the epidemiological evidence suggesting that the consumption of artificially sweetened beverages may be associated with higher body weights, there are also a range of physiological studies suggesting that artificial sweeteners can induce metabolic changes (including changes in taste preferences) that may promote weight gain.
Now, a study by Ameneh Madjd and colleagues from the University of Nottingham, UK, and the Tehran University of Medical Sciences, Iran (where the study was conducted) published in the American Journal of Clinical Nutrition, suggests that replacing ‘diet beverages’ (DBs) with water may not only result in greater weight loss but may also have greater benefits in terms of glucose metabolism.
The study was conduced in 89 women with overweight or obesity who usually consumed DBs in their diet.
Participants were randomized to either replace their DBs with water or continue drinking DBs 5 times/wk after their lunch for 24 wk (DB group) while on a 24-week weight-loss program.
71% of participants completed the trial (32 in the DB group, 30 in the water group).
Over the 24 weeks, the water group lost about 1.2 Kg more than the DB group (mean weight loss of both groups was about 8 Kg).
Improvements in fasting insulin levels, HOMA index and 2-hr post-prandial glucose also tended to be greater in the water than in the DB group.
Thus, the authors conclude that replacement of DBs with water after the main meal may lead to greater weight reduction and more favourable metabolic benefits during a weight-loss program.
As for the possible mechanisms that would account for these findings, the authors speculate based largely on self-reported changes in food intake that the water-drinking group may have been more compliant to the recommended diet and may have marginally reduced their carb intake. There is also the possibility that drinking water (rather than DBs) may support weight loss through other mechanisms.
Overall, I am not sure what to really make of this study. Clearly, being able to replace DBs with water may be beneficial. On the other hand, the more common problem in my practice is dealing with patients who consume larger amounts of sugar-sweetened beverages (SSBs rather than DBs) and I would imagine that if a shift to water is too drastic, DBs may at least be substantially better than continuing on with SSBs for these patients.
As Canada’s national representative in the World Obesity Federation (formerly IASO), the Canadian Obesity Network is proud to co-host the 13th International Congress on Obesity in Vancouver, 1-4 May 2016.
The comprehensive scientific program will span 6 topic areas:
Track 1: From genes to cells
- For example: genetics, metagenomics, epigenetics, regulation of mRNA and non–coding RNA, inflammation, lipids, mitochondria and cellular organelles, stem cells, signal transduction, white, brite and brown adipocytes
Track 2: From cells to integrative biology
- For example: neurobiology, appetite and feeding, energy balance, thermogenesis, inflammation and immunity, adipokines, hormones, circadian rhythms, crosstalk, nutrient sensing, signal transduction, tissue plasticity, fetal programming, metabolism, gut microbiome
Track 3: Determinants, assessments and consequences
- For example: assessment and measurement issues, nutrition, physical activity, modifiable risk behaviours, sleep, DoHAD, gut microbiome, Healthy obese, gender differences, biomarkers, body composition, fat distribution, diabetes, cancer, NAFLD, OSA, cardiovascular disease, osteoarthritis, mental health, stigma
Track 4: Clinical management
- For example: diet, exercise, behaviour therapies, psychology, sleep, VLEDs, pharmacotherapy, multidisciplinary therapy, bariatric surgery, new devices, e-technology, biomarkers, cost effectiveness, health services delivery, equity, personalised medicine
Track 5: Populations and population health
- For example: equity, pre natal and early nutrition, epidemiology, inequalities, marketing, workplace, school, role of industry, social determinants, population assessments, regional and ethnic differences, built environment, food environment, economics
Track 6: Actions, interventions and policies
- For example: health promotion, primary prevention, interventions in different settings, health systems and services, e-technology, marketing, economics (pricing, taxation, distribution, subsidy), environmental issues, government actions, stakeholder and industry issues, ethical issues
Early-bird registration is now open – click here
Abstract submission deadline is November 30, 2015 – click here
For more information including sponsorship and exhibiting at ICO 2016 – click here
I look forward to welcoming you to Vancouver next year.
In the meantime, Novo Nordisk, the maker of liraglutide, is continuing its development of a new GLP-1 analogue semaglutide as a once-weekly injection for the treatment of diabetes and obesity.
Last week the company released topline data from its SUSTAIN 3 study, a phase 3a trial in around 800 patients with type 2 diabetes randomized (open-label) to once-weekly semaglutide 1.0 mg vs. exenatide 2.0 mg (another once weekly GLP-1 analogue) over 56 weeks.
Participants on semaglutide achieved a greater reduction in A1c (1.5% vs. 0.9%; baseline = 8.4%) and weight loss (5.6 kg vs. 1.8 kg; baseline = 96 kg) compared to exenatide.
In general, adverse events (mainly GI-symptoms) were as expected for GLP-1 analogues with a rate of nausea twice as high with semaglutide compared to eventide (22% vs. 11%).
The overall discontinuation rate due to adverse events was slightly higher with semaglutide than eventide but fairly low overall (9.4% vs. 7.2%).
It should be noted that this was a diabetes and not an obesity study – so the almost 6% weight loss is indeed quite impressive (weight loss in studies designed to test drugs for obesity tends to be higher as patients are also advises to change their diet and physical activity).
According to Novo Nordisk, phase 2 dose-ranging trials of semaglutide in obesity could begin as early as next year – certainly an interesting development to watch.
Disclaimer: I have received honoraria as a consultant and speaker from Novo Nordisk
Thus, a study by Asheley Skinner and colleagues, published in the New England Journal of Medicine, shows that increased cardiometabolic risk is tightly linked with severe obesity both in children and young adults.
The study looks at cross-sectional data from overweight or obese children and young adults (3-19 yrs) who were included in the US National Health and Nutrition Examination Survey (NHANES) from 1999 through 2012.
Among 8579 children and young adults with a body-mass index at the 85th percentile or higher (according to the Centers for Disease Control and Prevention growth charts), 46.9% were overweight, 36.4% had class I obesity, 11.9% had class II obesity, and 4.8% had class III obesity.
Overall, for a given weight, males tended to have higher cardiometabolic risk than females.
Even after controlling for age, race or ethnic group, more severe obesity maps more likely to be associated with low HDL cholesterol level, high systolic and diastolic blood pressures, and high triglyceride and glycated hemoglobin levels.
Importantly, while this relationship was constantly present in males, the there were fewer significant differences in these variables according to weight category among female participants, suggesting that for a given body weight, girls were less likely to be at cardiometabolic risk compared to boys.
Thus, while body weight (or body fat) may not be a precise measure of individual health, the risk for having one or more cardiometabolic risk factor increases substantially with increasing severity of obesity.
However, it is also important to note that even in kids and youth with class III obesity, 70% of participants had normal lipids and about 90% of participants did not have elevated blood pressure or glycated hemoglobin.
This points to the fact that for a given body weight there is indeed wide variability in whether or not someone actually has cardiometabolic risk factors.
Thus, whether or not it makes sense to target every kid that presents with an elevated BMI for intervention, remains to be shown – most likely such an approach would probably not be cost-effective.
As in adults, it seems that interventions in kids are probably best targeted by global risk rather than simply by numbers on a scale.